An improved tabu algorithm applied to global optimizations of inverse problems in electromagnetics

This paper proposes an improved tabu search algorithm for global optimizations of multimodal functions with continuous variables of inverse problems in electromagnetics. The improvements include the introduction of a multistart process, the new neighborhood generating mechanism, and the memorization of the previously searched subspaces as well as the stop criteria for different termination purposes. The numerical results on solving a mathematical test function reveal that the proposed method is more robust in finding the global optimum compared with other kinds of tabu search algorithms. The shape optimization of an electrode demonstrates its value in practical engineering.